Abstract

Threat image projection (TIP) is a technology of current x-ray machines that allows exposing screeners to artificial but realistic x-ray images during the routine baggage x-ray screening operation. If a screener does not detect a TIP within a specified amount of time, a feedback message appears indicating that a projected image was missed. Feedback messages are also shown when a TIP image is detected or in the case of a non-TIP alarm, i.e. when the screener indicated that there was threat but in fact no TIP was shown. TIP data is an interesting source for quality control, risk analysis and assessment of individual screener performance. In two studies we examined the conditions for using TIP data for the latter purpose. Our results strongly suggest using aggregated data in order to have a large enough data sample as the basis for statistical analysis. Second, an appropriate TIP library containing a large number of threat items, which are representative for the prohibited items to be detected is recommended. Furthermore, consideration should be given to image-based factors such as general threat item difficulty, viewpoint difficulty, superposition and bag complexity. Different methods to cope with these issues are discussed in order to achieve reliable, valid and standardized measurements of individual screener performance using TIP.

Abstract

Threat image projection (TIP) is a technology of current x-ray machines that allows exposing screeners to artificial but realistic x-ray images during the routine baggage x-ray screening operation. If a screener does not detect a TIP within a specified amount of time, a feedback message appears indicating that a projected image was missed. Feedback messages are also shown when a TIP image is detected or in the case of a non-TIP alarm, i.e. when the screener indicated that there was threat but in fact no TIP was shown. TIP data is an interesting source for quality control, risk analysis and assessment of individual screener performance. In two studies we examined the conditions for using TIP data for the latter purpose. Our results strongly suggest using aggregated data in order to have a large enough data sample as the basis for statistical analysis. Second, an appropriate TIP library containing a large number of threat items, which are representative for the prohibited items to be detected is recommended. Furthermore, consideration should be given to image-based factors such as general threat item difficulty, viewpoint difficulty, superposition and bag complexity. Different methods to cope with these issues are discussed in order to achieve reliable, valid and standardized measurements of individual screener performance using TIP.

Download

Article Networks

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.